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Composite coating Al-FeCr-SiC/B4C on low-carbon steel prepared by mechanical milling and annealing: Tailoring coating microstructure and its oxidation properties

Alfian Noviyanto、Didik Aryanto、Nanda Hendra Pratama 等 7 位作者2026-08-18Next Materials

This study investigates the high-temperature cyclic oxidation behavior of low-carbon steel coated with Al–FeCr–SiC and Al–FeCr–B 4 C composite coatings prepared by mechanical milling followed by vacuum annealing at 600, 700, and 800 °C for 2 h. Annealing promoted microstructural consolidation and phase evolution, incl…

High-Temperature Coating BehaviorsAdvanced ceramic materials synthesisMetal and Thin Film Mechanics

Field-Theoretic Criterion for DRAM High-k Dielectrics: A Two-Dimensional Criterion Space (Soft-Mode × Bandgap) and Quantitative Doping-Pinning

Chao Qin2026-08-18Zenodo (CERN European Organization for Nuclear Research)

DRAM capacitor dielectrics face a hard leakage×EOT scaling constraint below the 1z-nm node (IMW 2020); for 30 years industry has responded by doping-pinning the tetragonal phase of high-k dielectrics (ZrO₂/HfO₂-based) to stabilize it—yet this long-standing practice lacks a unified criterion language. Using a field-the…

Ferroelectric and Piezoelectric MaterialsFerroelectric and Negative Capacitance DevicesSemiconductor materials and devices

Postmodern Physics of Hamzah Information.(190)

Sajad Jalali2026-08-18Zenodo (CERN European Organization for Nuclear Research)

تحلیل بنیادین، بازنویسی تانسوری و اثبات جامعِ کامل پارادوکس فرمیون‌های بدون جرم و چگالی جریان فوق‌شدید در نانومواد نیمه‌فلز وایل (The Massless Weyl Fermion Paradox and Ultra-High Current Density in Nanoscale Weyl Semimetals - معمای شماره ۳۰ از ۱۰۰) در بستر فیزیک اطلاعات حمزه (HIP-1155) به شرح زیر است: ۱. مقدمه و معمای…

Surface and Thin Film PhenomenaChemical and Physical Properties of MaterialsTopological Materials and Phenomena

Viscoelastic Response of Crosslinked Rubber: Coarse‐Grained Molecular Dynamics and Time‐Temperature Superposition

Kazuki HISAI、Yoshiaki Kawagoe、Tomonaga Okabe2026-08-18Macromolecular Theory and Simulations

ABSTRACT The viscoelastic response of crosslinked rubber was investigated using coarse‐grained molecular dynamics simulations combined with time‐temperature superposition. Crosslinked polymer networks containing different numbers of crosslinkers were generated using a dynamic reaction probability model and their mecha…

Polymer Nanocomposites and PropertiesPolymer crystallization and propertiesElasticity and Material Modeling

A new platform for achieving long-term air-stable long persistent luminescence in amorphous organic system

Zhenjiang Liu、Yunshu Meng、Zhihe Chi 等 15 位作者2026-08-18Light Science & Applications

Organic long persistent luminescence (OLPL) materials are at the forefront of research, undergoing rapid evolution due to their extensive potential applications. The realization of hour-level OLPL, particularly an air-stable one, remains a significant challenge. Here, we developed a new platform to achieve long-term a…

Luminescence and Fluorescent MaterialsSynthesis and Properties of Aromatic CompoundsOrganic Light-Emitting Diodes Research

Influence of polyaniline (PANI) incorporation on the structural, optical, AC conductivity and LPG sensing of SnO2 thin films

Anisha Joseph、S. Deepa、Benoy Skariah 等 4 位作者2026-08-18Next Nanotechnology

Metal oxide thin film gas sensors have got wide acceptance due to their sensitivity, stability, rapid response-recovery, mechanical and thermal stability, repeatability, reproducibility, crystallinity etc. In the present work pristine and polyaniline (PANI) incorporated SnO 2 thin films were successfully fabricated by…

Polymer Nanocomposite Synthesis and IrradiationConducting polymers and applicationsGas Sensing Nanomaterials and Sensors

Processable polyaniline modified biodegradable substrates as the electrode material for gas sensor application

P. C. Himadri Reddy、M. S. Sunitha、Saravanan Chandrasekaran2026-08-18Frontiers in Sensors

Gas sensors are extremely important because of their broad application in industrial production and everyday life. However, many conventional gas sensors require high operating temperatures and are fabricated from non-biodegradable materials, leading to increased energy consumption and disposal concerns. To address th…

Advanced Chemical Sensor TechnologiesConducting polymers and applicationsGas Sensing Nanomaterials and Sensors

Mixed-Variable Autonomous Catalyst Search Model (MACSM)

Begüm Yıldırım2026-08-18Zenodo (CERN European Organization for Nuclear Research)

This paper develops a revised mathematical solution framework for the chemistry challenge "Can autonomous laboratories discover catalysts and operating waveforms together rather than optimizing them separately?". The proposed Mixed-Variable Autonomous Catalyst Search Model (MACSM) was constructed after an earlier form…

Catalysis and Oxidation ReactionsCatalytic Processes in Materials ScienceMachine Learning in Materials Science

Effect of Lanthanum Incorporation on the Structural, Surface, and Thermal Properties of Nickel-Co-Doped Alumina and Silica Oxides

Yash Mishra、D. Mandal2026-08-18ChemRxiv

Rare-earth-promoted transition metal oxides have attracted significant attention owing to their ability to modify structural, textural, and surface characteristics of functional ceramic materials. In the present work, lanthanum and nickel co-doped oxide systems supported on alumina (Al2O3) and silica (SiO2) were synth…

Advanced ceramic materials synthesisAdvancements in Solid Oxide Fuel CellsAerogels and thermal insulation

Nitrogen Doping Reduces the Neurotoxic Effects of Graphene Quantum Dots by Suppressing Proinflammatory and Oxidative Stress Pathways

Priyanka Tiwari、Gorantla Vikas Babu、Vikrant Rahi 等 5 位作者2026-08-18ACS Chemical Neuroscience

Abstract Graphene quantum dots (GQDs) and their nitrogen-doped counterparts (N-GQDs) have recently been explored in the management of neurological disorders. However, their biocompatibility remains questionable, particularly subsequent to direct brain exposure. In this study, we investigated the neurotoxicity of GQDs…

Quantum Dots Synthesis And PropertiesGraphene and Nanomaterials ApplicationsCarbon and Quantum Dots Applications

Golden Ratio and Five-Fold Symmetry in Quasicrystals via Penrose Tilings — E8 Intelligence Research

Andrew Stewart Caldin2026-08-18Zenodo (CERN European Organization for Nuclear Research)

FINDING: Five-fold rotational symmetry is forbidden in periodic lattices but emerges in quasicrystals via aperiodic tiling governed by the golden ratio. MATH: Golden ratio φ = (1+√5)/2 ≈ 1.618; its reciprocal φ⁻¹ ≈ 0.618; complex golden ratio ζ = e^(iπ/5) = φ/2 + i√(3-φ)/2 (a 5th root of unity). Penrose tilings use tw…

Quasicrystal Structures and PropertiesCrystal Structures and PropertiesAdvanced Mathematical Theories and Applications

Balanced Fire Safety and Mechanical Integrity in Thermoplastic Polyurethane via a Synergistic Ternary System of Hydromagnesite andMicroencapsulated Additives

Yongbing Yuan、Junkang Shi、Wenli Tan 等 8 位作者2026-08-18Journal of Applied Polymer Science

ABSTRACT To mitigate the trade‐off between flame retardancy and mechanical performance in thermoplastic polyurethane (TPU), an optimized ternary flame‐retardant formulation consisting of hydromagnesite (HM), microencapsulated red phosphorus (MRP), and microencapsulated expandable graphite (MEG) was developed. The ther…

Fire dynamics and safety researchFlame retardant materials and propertiesPolymer composites and self-healing

Surface and structural characteristics of cast NiTi alloy impacted by submerged cavitating waterjet

Jie Chen、Hai-xia Liu、Guang-Lei Liu 等 6 位作者2026-08-18China Foundry

The NiTi alloy has great application potential in the engineering fields involving cavitation. The present study aims to reveal variations in surface and structure characteristics of the NiTi alloy subjected to submerged waterjet. Effects of the standoff distance and cavitation treatment duration were investigated. Th…

Shape Memory Alloy TransformationsSurface Treatment and Residual StressCavitation Phenomena in Pumps

Estimation of the Pre-Exponential Factor and Conversion Function of Solid-State Reactions Using the Vyazovkin Isoconversional Method

Alireza Aghili2026-08-18ChemRxiv

The Vyazovkin isoconversional method is widely regarded as a reliable model-free approach for the kinetic analysis of solid-state reactions. However, its direct application is primarily limited to the determination of the activation energy, while the pre-exponential factor and conversion function generally require add…

Chemical Thermodynamics and Molecular StructureThermal and Kinetic AnalysisPolymer crystallization and properties

TP-Agent: A LLM Agent for Frontier Theoretical Physics Research

Peng Wang2026-08-18Zenodo (CERN European Organization for Nuclear Research)

We present TP-Agent, an autonomous LLM-based agent utilizing a Plan–Execute–Reflect architecture and external computational tools (Python, Mathematica) to assist in theoretical physics research. We evaluate it on two benchmarks: the comprehensive TPBench and the frontier-level PRL-Bench. While TP-Agent demonstrates st…

Scientific Computing and Data ManagementMachine Learning in Materials ScienceComputational Physics and Python Applications

Microstructural evolution of SIMP steel during martensitic transformation

Y.L. Zhang、Hongpeng Zhang、Chen Dong 等 8 位作者2026-08-18Materials & Design

SIMP steel, a reduced activation ferritic/martensitic heat–resistant steel, is a promising candidate for structural applications in future nuclear fusion reactors. Understanding the evolution of microstructure in SIMP steel is of practical importance for improving the structural integrity of components made from this…

Fusion materials and technologiesMagnetic Properties and ApplicationsMicrostructure and Mechanical Properties of Steels

Algorithmic Discovery of Room-Temperature Superconductor Candidates via Topological Stress Filtering in Causal-AI Networks

László János Németh2026-08-18Zenodo (CERN European Organization for Nuclear Research)

The precise geometric and topological mechanisms governing high-temperature and potential room-temperature superconductivity (RTS) remain obscured by the mathematical rigidity of continuous differential equations. In this paper, we operationalize the theoretical premise that superconductivity is not merely a quantum p…

Machine Learning in Materials ScienceTopological Materials and PhenomenaQuantum many-body systems

Evaluation of the Electrochemical Performance of MXene-Based Nanocomposites for Supercapacitor Applications

Ruvini L. Guniyangodage Dona、Xin Chang、Shaneel Chandra2026-08-18Applied Sciences

Supercapacitors offer high power density, fast charging/discharging capability, and long cycle life, yet their relatively low energy density limits broader deployment in electric vehicles, portable electronics, and grid storage systems. MXenes, a family of two-dimensional transition metal carbides, nitrides, and carbo…

Supercapacitor Materials and FabricationMXene and MAX Phase MaterialsElectromagnetic wave absorption materials

Straightforward Assessment of Structural Disorder in Ti3C2T x MXene Using Raman Spectroscopy: Implications for Defect Engineering

André L. A Marinho、Marie‐Laure David、Noé Condé 等 15 位作者2026-08-18ACS Applied Nano Materials

Abstract MXenes, a large family of two-dimensional transition-metal carbides and nitrides, have attracted considerable interest owing to their unique physicochemical properties. Structural defects play a key role in tuning these properties, yet their characterization remains highly challenging. Herein, controlled Ne2+…

2D Materials and ApplicationsMXene and MAX Phase MaterialsGraphene research and applications

Uncertainty-Aware Metrics: Code and Synthetic Datasets

Mohammad Abbas、Mārtiņš Zaumanis2026-08-18Zenodo (CERN European Organization for Nuclear Research)

Here you can download the code and synthetic data used in the article: "Uncertainty-Aware Metrics for Evaluating Machine Learning Regression Models in Materials Testing".

Explainable Artificial Intelligence (XAI)Adversarial Robustness in Machine LearningMachine Learning in Materials Science